State of the Art of Deep Learning Technology and its Next Generation Architecture

Shorterm Memory AI model shows that during the silent period of memory, the brain can use the short-term plasticity of synaptic connections between neurons to memorize information.CGRA computing energy efficiency can reach 1000 times of CPU computing architecture,100-1000 times of GPU computing architecture, and more than 100 times of FPGA computing architecture.FpgaConvNet, ALAMO and Snowflake are mainly concerned with the feature extractor part of CNN.DeepBurning and FP-DNN support recurrent neural network (RNN) and long-term and short-term memory (LSTM) networks.In a paper in Physical Review X, MIT researchers describe a new photon accelerator that uses optical components and optical signal processing technology to reduce chip size, which will allow the chip to expand to neural networks several orders of magnitude larger than electrical chips. By taking hardware performance and power consumption as indicators in the training phase, hardware adjustable parameters, model weight and topology will be jointly modified in the optimization process to jointly optimize the application-level accuracy and the required reasoning execution time and power consumption.Artificial intelligence with deep learning architecture is still in infancy. But it has already brought a lot of help to mankind

GaussianDiffusion: 3D Gaussian Splatting for Denoising Diffusion Probabilistic Models with Structured Noise

Text-to-3D, known for its efficient generation methods and expansive creative potential, has garnered significant attention in the AIGC domain. However, the amalgamation of Nerf and 2D diffusion models frequently yields oversaturated images, posing severe limitations on downstream industrial applications due to the constraints of pixelwise rendering method. Gaussian splatting has recently superseded the traditional pointwise sampling technique prevalent in NeRF-based methodologies, revolutionizing various aspects of 3D reconstruction. This paper introduces a novel text to 3D content generation framework based on Gaussian splatting, enabling fine control over image saturation through individual Gaussian sphere transparencies, thereby producing more realistic images. The challenge of achieving multi-view consistency in 3D generation significantly impedes modeling complexity and accuracy. Taking inspiration from SJC, we explore employing multi-view noise distributions to perturb images generated by 3D Gaussian splatting, aiming to rectify inconsistencies in multi-view geometry. We ingeniously devise an efficient method to generate noise that produces Gaussian noise from diverse viewpoints, all originating from a shared noise source. Furthermore, vanilla 3D Gaussian-based generation tends to trap models in local minima, causing artifacts like floaters, burrs, or proliferative elements. To mitigate these issues, we propose the variational Gaussian splatting technique to enhance the quality and stability of 3D appearance. To our knowledge, our approach represents the first comprehensive utilization of Gaussian splatting across the entire spectrum of 3D content generation processes

The evolutionary random interval fingerprint for a more secure wireless communication

[[abstract]]In this paper, we propose a novel evolutionary Random Interval Fingerprint (RIF) for active RFID and ZigBee systems. This new approach can enable more secure multi-party communication since, if the wireless packets are forged by another wireless communication party, the interval fingerprint can provide another way to detect the spoofing packet. Moreover, the random evolutionary algorithms, both genetic and memetic, are also proposed as a means to generate the random interval fingerprint. Compared to the conventional random generator, our approach is flexible in generating uniform random and long cycle numbers, and more robust for the anti-cracking. It is difficult for the forged party to produce the fake random intervals. Finally, we provide an application example, a completed work survey, pseudo-code and analysis result to prove that our concept is feasible for the Wireless communication.[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子

Sparse Matrix for ECG Identification with Two-Lead Features

Electrocardiograph (ECG) human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods

Spatial modelling and mapping of teen birth rates in Taiwan in the period 1995-2010

Geographical variations in teen birth rates (TBR) still persist despite controlling for contextual factors. The aim of this research was to identify spatial patterns of TBR in Taiwan and to examine spatial relationships among different contextual factors. Using townships as the unit of analysis (N=359), this research used social and demographic variables for the years 1995, 2000, 2005 and 2010 and conducted spatial modelling of TBR. Geographical maps of TBR were presented, and Local Indicator of Spatial Autocorrelations was used to identify TBR clustering. Comparisons were made between ordinary least-squares models and spatial lag models, in which township-level TBRs were regressed on other township-level contextual characteristics. Our study found that townships with a high TBR were mostly in eastern, central and some southern regions of Taiwan, while townships with a low TBR were in the vicinity of metropolitan areas. The significant spatial lag indicated that townships would have a higher expected prevalence rate if adjacent townships have had higher rates. Results also indicated that the percentage of aborigines and the percentage of college-educated people were consistently associated with TBR over the years. Interventions aimed at reducing TBR in Taiwan should consider the presence of spatial correlations and should incorporate neighbouring townships

Signal Waveform Detection with Statistical Automaton for Internet and Web Service Streaming

In recent years, many approaches have been suggested for Internet and web streaming detection. In this paper, we propose an approach to signal waveform detection for Internet and web streaming, with novel statistical automatons. The system records network connections over a period of time to form a signal waveform and compute suspicious characteristics of the waveform. Network streaming according to these selected waveform features by our newly designed Aho-Corasick (AC) automatons can be classified. We developed two versions, that is, basic AC and advanced AC-histogram waveform automata, and conducted comprehensive experimentation. The results confirm that our approach is feasible and suitable for deployment

Contextual factors and spatial patterns of childhood malnutrition in provinces of Burkina Faso

Background: Approximately 45% of all children's deaths are associated with malnutrition, and sub-Saharan Africa is hardest hit by this phenomenon. However, information on geographical variations of malnutrition in developing countries is limited. This study examined the geographical distribution and community characteristics associated with child malnutrition in Burkina Faso. Design: Data from the 2011 Burkina Faso Demographic Health Survey were analyzed. A general Kriging interpolation method was used to generate spatial malnutrition patterns. The global Moran's I test was used to identify significant malnutrition spatial patterns. Generalized estimating equations (GEEs) were fitted to examine the association between community level factors and malnutrition. Results: Average rates of stunting and wasting in the communities were 32.48% and 15.05%, respectively. Stunting hotspots were observed in the eastern and northeastern parts of Burkina Faso (i.e. Oudolan, Séno and Yagha, among others), while high rates of wasting were observed in the north-central part. The GEE results revealed lower stunting rates in communities with a higher percentage of households with improved sanitation. Communities with higher rates of professionally assisted births were associated with low wasting rates, while communities with higher rates of households with a low wealth index reported higher rates of wasting. Conclusions: Spatial statistical models of malnutrition prevalence are useful for indicating hotspots over wide areas and hence, for guiding intervention strategies. This study revealed significant geographical patterns and community factors associated with childhood malnutrition. These factors should be considered in future programs aimed at reducing malnutrition in Burkina Faso

High myopia at high altitudes

Background: Optic nerve sheath diameter (ONSD) increases significantly at high altitudes, and is associated with the presence and severity of acute mountain sickness (AMS). Exposure to hypobaria, hypoxia, and coldness when hiking also impacts intraocular pressure (IOP). To date, little is known about ocular physiological responses in trekkers with myopia at high altitudes. This study aimed to determine changes in the ONSD and IOP between participants with and without high myopia (HM) during hiking and to test whether these changes could predict symptoms of AMS.Methods: Nine participants with HM and 18 without HM participated in a 3-day trek of Xue Mountain. The ONSD, IOP, and questionnaires were examined before and during the trek of Xue Mountain.Results: The ONSD values increased significantly in both HM (p = 0.005) and non-HM trekkers (p = 0.018) at an altitude of 1,700 m. In the HM group, IOP levels were greater than those in the non-HM group (p = 0.034) on the first day of trekking (altitude: 3,150 m). No statistically significant difference was observed between the two groups for the values of ONSD. Fractional changes in ONSD at an altitude of 1,700 m were related to the development of AMS (rpb = 0.448, p = 0.019) and the presence of headache symptoms (rpb = 0.542, p = 0.004). The area under the ROC curve for the diagnostic performance of ONSD fractional changes at an altitude of 1,700 m was 0.859 for predicting the development of AMS and 0.803 for predicting the presence of headache symptoms.Conclusion: Analysis of changes in ONSD at moderate altitude could predict AMS symptoms before an ascent to high altitude. Myopia may impact physiological accommodation at high altitudes, and HM trekkers potentially demonstrate suboptimal regulation of aqueous humor in such environments